JSON Conversion FAQ: Complete Format Conversion Guide
Expert answers to JSON conversion questions • Updated March 2025
🚀 TL;DR - Quick Answers
JSON to XML Conversion
Converting JSON to XML online is straightforward with the right tools:
Step-by-Step Process
- Choose a converter: Use JsonViewer.tools, ConvertJSON.com, or similar
- Input your JSON: Paste, upload file, or provide URL
- Configure options: Set root element name, attributes handling
- Convert and download: Get your XML file instantly
Top JSON to XML Converters
- Clean interface
- Instant conversion
- Proper XML formatting
- Error handling
- Simple conversion
- File upload support
- Download options
- Multiple formats
- Specialized tool
- Advanced options
- Batch processing
- API access
Conversion Example
JSON Input:
{
"user": {
"name": "John Doe",
"age": 30,
"email": "john@example.com",
"hobbies": ["reading", "coding"]
}
}
XML Output:
<?xml version="1.0" encoding="UTF-8"?>
<root>
<user>
<name>John Doe</name>
<age>30</age>
<email>john@example.com</email>
<hobbies>
<item>reading</item>
<item>coding</item>
</hobbies>
</user>
</root>
JSON and XML are both data interchange formats, but they have significant differences:
Structure and Syntax
Aspect | JSON | XML |
---|---|---|
Syntax | Lightweight, key-value pairs | Tag-based markup language |
Data Types | String, Number, Boolean, Array, Object, null | All data as text (with type attributes) |
Attributes | Not supported | Supported (tag attributes) |
Namespaces | Not supported | Fully supported |
Comments | Not allowed | Supported |
File Size | Smaller (less verbose) | Larger (more verbose) |
Advantages and Use Cases
JSON Advantages
- Lightweight: Less bandwidth usage
- Native JavaScript support: Direct parsing
- Human readable: Easy to read and write
- Simple structure: Quick to learn
- Fast parsing: Better performance
Best for:
- Web APIs and REST services
- Configuration files
- Data exchange between applications
- Mobile applications
XML Advantages
- Extensible: Custom tags and attributes
- Schema validation: XSD support
- Namespaces: Avoid naming conflicts
- Metadata support: Rich attribute system
- Document structure: Better for documents
Best for:
- Document markup (HTML-like)
- Enterprise systems (SOAP)
- Configuration with validation
- Data with complex relationships
Example Comparison
Same Data in JSON:
{
"book": {
"title": "JSON Guide",
"author": "John Smith",
"isbn": "978-1234567890",
"price": 29.99,
"available": true,
"categories": ["programming", "web"]
}
}
Same Data in XML:
<?xml version="1.0" encoding="UTF-8"?>
<book isbn="978-1234567890" available="true">
<title>JSON Guide</title>
<author>John Smith</author>
<price currency="USD">29.99</price>
<categories>
<category>programming</category>
<category>web</category>
</categories>
</book>
XML can usually be converted to JSON, but some XML features don't have direct JSON equivalents:
Conversion Challenges
XML attributes need special handling in JSON:
<user id="123" active="true">John</user>
{
"user": {
"@id": "123",
"@active": "true",
"#text": "John"
}
}
XML with text and elements mixed:
<p>Hello <strong>world</strong> today!</p>
{
"p": [
"Hello ",
{"strong": "world"},
" today!"
]
}
XML namespaces require special JSON representation:
<book xmlns:pub="http://publisher.com">
<pub:publisher>Tech Books</pub:publisher>
</book>
{
"book": {
"@xmlns:pub": "http://publisher.com",
"pub:publisher": "Tech Books"
}
}
Conversion Strategies
- Attribute prefixes: Use @ for attributes (@id, @class)
- Text content: Use #text for mixed content
- Array handling: Single elements may become arrays
- Data type preservation: All XML data becomes strings
Best Practices
- Choose conversion tools that handle your specific XML features
- Test with sample data before bulk conversion
- Consider data loss in attributes and namespaces
- Validate converted JSON structure
JSON to CSV/Excel Conversion
Converting JSON to CSV flattens hierarchical data into tabular format:
Online Conversion Process
- Select a converter: Use JsonViewer.tools, ConvertCSV, or similar
- Input JSON data: Paste or upload your JSON file
- Configure flattening: Choose how to handle nested objects
- Download CSV: Get ready-to-use CSV file
Flattening Strategies
Nested properties become dot-separated columns:
{
"user": {"name": "John", "address": {"city": "NYC"}}
}
CSV Columns:
user.name, user.address.city
John, NYC
Arrays create multiple rows or columns:
{
"name": "John",
"hobbies": ["reading", "coding"]
}
CSV (Multiple Rows):
name, hobby
John, reading
John, coding
Complex objects remain as JSON strings:
{
"name": "John",
"metadata": {"tags": ["a", "b"], "score": 95}
}
CSV:
name, metadata
John, "{""tags"":[""a"",""b""],""score"":95}"
Best Online JSON to CSV Tools
Tool | Features | Best For |
---|---|---|
JsonViewer.tools | Clean UI, instant conversion, proper flattening | General use, simple JSON |
ConvertCSV | Advanced options, custom delimiters, large files | Complex JSON, bulk conversion |
JSON-CSV | API access, batch processing, custom mapping | Automated workflows |
There are several ways to convert JSON to Excel format:
Method 1: Direct Online Conversion
- Use online converters like JsonViewer.tools
- Upload or paste your JSON data
- Select Excel (.xlsx) as output format
- Download the converted Excel file
Method 2: JSON → CSV → Excel
- Convert JSON to CSV first
- Open Excel
- Import CSV file (Data → From Text/CSV)
- Configure column types and formatting
Method 3: Excel Power Query
Excel's built-in feature for JSON import:
- Open Excel
- Go to Data → Get Data → From File → From JSON
- Select your JSON file
- Use Power Query Editor to transform data
- Load data into worksheet
Power Query Advantages:
- Native Excel feature
- Powerful data transformation
- Handles complex nested structures
- Refreshable data connections
Handling Complex JSON in Excel
Power Query can expand nested objects into separate columns automatically.
Arrays can be expanded into multiple rows or kept as comma-separated values.
Excel can auto-detect and convert data types (numbers, dates, text).
Conversion Example
JSON Input:
[
{
"id": 1,
"name": "John Doe",
"email": "john@example.com",
"orders": [
{"date": "2025-01-15", "amount": 150.00},
{"date": "2025-02-10", "amount": 89.99}
]
},
{
"id": 2,
"name": "Jane Smith",
"email": "jane@example.com",
"orders": [
{"date": "2025-01-20", "amount": 200.00}
]
}
]
Excel Output (Flattened):
id | name | orders.date | orders.amount | |
---|---|---|---|---|
1 | John Doe | john@example.com | 2025-01-15 | 150.00 |
1 | John Doe | john@example.com | 2025-02-10 | 89.99 |
2 | Jane Smith | jane@example.com | 2025-01-20 | 200.00 |
Yes, Excel can open JSON files using several methods:
Method 1: Power Query (Recommended)
Steps:
- Open Excel
- Navigate to Data tab → Get Data → From File → From JSON
- Browse and select your JSON file
- Power Query Editor opens automatically
- Transform data as needed
- Click Close & Load to import
Power Query Features:
- Automatic structure detection
- Data type conversion
- Column expansion options
- Filter and transform capabilities
Method 2: Direct File Opening
Excel 365 and newer versions can open JSON files directly:
- Use File → Open
- Select JSON file
- Excel automatically launches Power Query
- Follow the transformation wizard
Method 3: Import from Web
For JSON data from URLs:
- Go to Data → From Web
- Enter JSON API URL
- Excel fetches and parses JSON
- Transform in Power Query Editor
Excel Versions Compatibility
Excel Version | JSON Support | Method |
---|---|---|
Excel 365 | Full native support | Power Query built-in |
Excel 2019/2021 | Good support | Power Query available |
Excel 2016 | Limited support | Power Query add-in required |
Excel 2013 or older | No native support | Convert to CSV first |
Common Issues and Solutions
Excel has row limits (1M+ rows). Consider splitting large files or using database imports.
Deep nesting may require multiple expand operations in Power Query.
Manually set column types in Power Query for better data handling.
Advanced JSON Conversion
YAML is a human-readable data serialization standard, often used for configuration files:
JSON to YAML Conversion Process
- Use online converters like JsonViewer.tools or YAML converters
- Paste your JSON data
- Get YAML output with proper indentation
- Copy or download the YAML file
Conversion Example
JSON Input:
{
"database": {
"host": "localhost",
"port": 5432,
"name": "myapp",
"credentials": {
"username": "admin",
"password": "secret"
},
"options": {
"ssl": true,
"timeout": 30,
"pool_size": 10
}
},
"features": ["auth", "logging", "caching"]
}
YAML Output:
database:
host: localhost
port: 5432
name: myapp
credentials:
username: admin
password: secret
options:
ssl: true
timeout: 30
pool_size: 10
features:
- auth
- logging
- caching
Key Differences: JSON vs YAML
Feature | JSON | YAML |
---|---|---|
Syntax | Brackets and quotes | Indentation-based |
Comments | Not supported | Supported (#) |
Multiline strings | Escaped characters | Native support (| and >) |
Human readable | Good | Excellent |
File size | Smaller | Larger |
When to Use YAML
- Configuration files: Docker Compose, Kubernetes, CI/CD
- Documentation: More readable than JSON
- Data exchange: When human editing is needed
- Templates: Infrastructure as Code
JSON can be converted to and from many different data formats:
Common Format Conversions
Structured Data Formats
Hierarchical data exchange
- Web services
- Configuration files
- Data migration
Human-readable configuration
- DevOps configs
- Documentation
- CI/CD pipelines
Configuration files
- Package managers
- Project configs
- Settings files
Tabular Data Formats
Spreadsheet compatibility
- Data analysis
- Excel import/export
- Database loading
Tab-separated values
- Database imports
- Data processing
- Analytics tools
Spreadsheet format
- Business reports
- Data visualization
- Financial analysis
Binary/Specialized Formats
Efficient serialization
- API communication
- Microservices
- High-performance apps
Binary JSON-like format
- Network protocols
- Data storage
- Real-time systems
Schema evolution
- Big data processing
- Data pipelines
- Apache ecosystem
Conversion Tools by Category
Online Converters
- JsonViewer.tools: JSON, XML, CSV, YAML
- ConvertJSON.com: Multiple format support
- Online-Convert.com: Various data formats
Programming Libraries
- Python: json, yaml, csv, pandas libraries
- JavaScript: JSON.parse/stringify, js-yaml, csv-parser
- Java: Jackson, Gson, SnakeYAML
Command Line Tools
- jq: JSON processing and conversion
- yq: YAML processing (similar to jq)
- csvkit: CSV manipulation and conversion
🎯 Key Takeaways
Format Selection
Choose the right format: JSON for APIs, XML for documents, CSV for spreadsheets, YAML for configs.
Conversion Tools
Use online converters for quick tasks, programming libraries for automation, Excel Power Query for business use.
Data Structure
Understand how nested JSON translates to flat formats - some data relationships may be lost or transformed.
Validation
Always validate converted data to ensure accuracy and completeness after format transformation.